--- date: January 16, 2026 · slug: inside-git ---
In the previous post, we learnt [How Git manages version control](post.html?post=git-essentials) through its internal structures. In this continuation, we will delve deeper into h
cat inside-git.md →~/blog — ls -la *.md11 posts
--- date: January 13, 2026 · slug: git-essentials ---
If you have ever played a video game, you know the anxiety of facing a difficult boss. What is the first thing you do before walking through that boss door? You save your game. W
cat git-essentials.md →--- date: January 10, 2026 · slug: why-version-control-exists ---
## Why Version Control Exists - The Pendrive Problem **Analogy: The Pendrive Problem** Let's imagine a world where version control systems like Git do not exist. Instead, develo
cat why-version-control-exists.md →--- date: Mar 21, 2025 · slug: automate-unit-tests-using-ci-cd ---
In this blog, we’ll explore how to set up a complete CI/CD pipeline using `Jenkins`, `pytest`, and `Terraform` to automate unit testing and deployment for AWS Glue and Lambda jobs
cat automate-unit-tests-using-ci-cd.md →--- date: Feb 7, 2025 · slug: spark-application-lifecycle-outside ---
In this blog, we will go in-depth on the overall life cycle of Spark Applications from outside the actual Spark code. Before going ahead, I recommend reading the [Execution Modes]
cat spark-application-lifecycle-outside.md →--- date: Feb 6, 2025 · slug: spark-execution-modes ---
In this post, we will discuss the different execution modes available in Apache Spark. Apache Spark provides three execution modes to run Spark applications: Cluster mode, Client mode, and Local mode.
cat spark-execution-modes.md →--- date: Jan 21, 2025 · slug: spark-job-anatomy ---
Understanding the internal execution flow of a Spark application is key to optimizing performance and debugging. This blog dives into the details of Spark jobs, stages, and tasks, providing a thorough exploration of how Spark handles distributed execution.
cat spark-job-anatomy.md →--- date: Jan 13, 2025 · slug: handling-nulls-in-spark ---
In SQL null is a special marker used to indicate that a data value does not exist in the database. A null should not be confused with a value of 0. Let's deep dive into handling nulls in Spark.
cat handling-nulls-in-spark.md →--- date: Jan 10, 2025 · slug: columns-and-expressions ---
Apache Spark's Column and Expression play a big role in making your pipeline more efficient. In this blog we will look into ALL the possible ways to select columns, use built-in functions and perform calculations with column objects and expressions in PySpark.
cat columns-and-expressions.md →--- date: Jan 1, 2025 · slug: spark-basics ---
Welcome to my Apache Spark series! I'll dive deep into Apache Spark, from basics to advanced concepts. This series is about learning, exploring, and sharing—documenting my journey to mastering Apache Spark.
cat spark-basics.md →--- date: Nov 26, 2024 · slug: welcome-to-my-blog ---
Welcome to my blog! This is where I'll be sharing my thoughts, experiences, and insights on technology, development, and more.
cat welcome-to-my-blog.md →